A high-performance, distributed, in-memory key-value cache store for speeding up dynamic web applications.
Memcached is a high-performance, distributed, in-memory key-value cache store designed to speed up dynamic web applications by reducing database load. It stores frequently accessed data in memory, allowing applications to retrieve data much faster than from disk-based databases. The system is multithreaded and event-based, optimized for handling large volumes of concurrent requests in distributed environments.
Developers and system administrators building high-traffic web applications that need to reduce database load and improve response times. Particularly useful for teams working on distributed systems where caching across multiple servers is necessary.
Developers choose Memcached for its proven performance, simplicity, and reliability as a distributed caching solution. Its minimal resource overhead, straightforward protocol, and extensive community support make it a go-to choice for accelerating web applications without complex setup or maintenance.
memcached development tree
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Optimized for high concurrency and fast in-memory operations, as highlighted in the key features for handling large volumes of requests in distributed systems.
Designed from the ground up for deployment across multiple servers, making it ideal for scalable web applications without complex client-side logic.
Uses a straightforward protocol that's easy to integrate, with optional TLS support for secure connections, as mentioned in the dependencies and build options.
Supports mlockall to prevent swapping, ensuring cache performance isn't degraded by disk I/O, though the README warns it can be dangerous with large caches.
Enabling TLS or the proxy requires additional dependencies and build steps, such as installing OpenSSL and running vendor fetch scripts, which complicates setup compared to drop-in solutions.
Data is stored only in memory and lost on restart, lacking built-in persistence or replication mechanisms, which might not suit applications requiring data durability.
The README directs users to a mailing list for questions, noting that GitHub issues aren't seen by everyone, potentially slowing down support and troubleshooting.